Following the medical image segmentation literature, we use two main metrics for evaluation: dice coefficient and average symmetric surface distance (ASSD). The Dice coefficient is a popular choice in medical image analysis works which measures semantic segmentation quality [1]}, [2]}, [3]}. It is used for direct evaluation of segmentation map accuracy. The average symmetric surface distance is a metric which has been used [4]}, [2]}, [6]} to assess the quality of borders of predicted segmentation maps which are important for diagnosis. A good segmentation will have a large Dice coefficient and low ASSD value, the desirability of a result being application dependant.
